Systems and methods for multi-user mutli-lingual communications

ABSTRACT

Various embodiments described herein facilitate multi-lingual communications. The systems and methods of some embodiments may enable multi-lingual communications through different modes of communications including, for example, Internet-based chat, e-mail, text-based mobile phone communications, postings to online forums, postings to online social media services, and the like. Certain embodiments may implement communications systems and methods that translate text between two or more languages (e.g., spoken), while handling/accommodating for one or more of the following in the text: specialized/domain-related jargon, abbreviations, acronyms, proper nouns, common nouns, diminutives, colloquial words or phrases, and profane words or phrases.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/433,513, filed Feb. 15, 2017, which is a continuation of U.S.application Ser. No. 13/763,565, filed Feb. 8, 2013 (now U.S. Pat. No.9,600,473, issued Mar. 21, 2017), the entire contents of each of whichare hereby incorporated by reference.

BACKGROUND 1. Technical Field

The present invention(s) generally relate to communications and, moreparticularly, communications across the world involving multiple usersand multiple languages.

2. Description of Related Art

Before the advent of machine-based language translations (hereafter,“machine translations”), translation between two languages was onlypossible via intervention or interpretation by a person educated in bothlanguages. In contrast, typical machine translators operate based onstatistical/stochastic analysis of context and grammar, usually withoutneed of human intervention/interpretation.

Typical machine translation is often error prone, particularly where thetext to be translated has a minimal context. Text having minimal contextis often found in conversations, which employ brief sentenceconstruction. Additionally, machine translations often have trouble withabbreviations, acronyms, diminutives, colloquial words/phrases, propernouns, and common nouns, which are also commonly found in conversationaltext.

SUMMARY

Various embodiments described herein provide for systems and methodsthat relate to multi-lingual communications between multiple users,possibly where the users are at two or more client systems. Modes ofcommunications facilitated by embodiments may include Internet-basedchat (e.g., Apple® iMessage, Windows® Live Messenger, etc.), e-mail(e.g., embedded forum messaging, Yahoo® mail, RFC 5322, etc.),text-based mobile phone communications (e.g., SMS messages or MMSmessages), postings to online forums (e.g., postings to a web-basedhobby forum), and postings to online social media services (e.g.,Twitter®, Facebook®, etc.). For example, systems and methods mayimplement a multi-lingual, multi-user chat system.

For some embodiments, the method provided comprises identifying a firstlanguage and a second language, receiving an initial message in thefirst language from a first person at a first chat client system whocommunicates in the first language, and querying a data store for afirst corresponding message, in the second language, that is based onthe initial message in the first language. If the data store includesthe first corresponding message, the method may then assist in sendingthe corresponding message to a second person at a second chat clientsystem who communicates in the second language. Depending on theembodiment, the initial message may comprise text, an emoticon,ASCII-based art, or other content suitable or customary for ahuman-readable message sent over a network. Additionally, the initialmessage may be part of a larger message being communicated between chatclient systems (e.g., the initial message is one sentence in amulti-sentence message).

If the data store does not include the first corresponding message, themethod may utilize a transformation engine to attempt to transform atleast a portion of the initial message to a transformed message in thefirst language. Using the transformed message, the method may then querythe data store for a second corresponding message, in the secondlanguage, that is based on the transformed message.

For certain embodiments, the system or method may attempt transformingthe initial message using a series of transformation operations beforequerying the data store is queried for a second corresponding messagethat is based on the transformed message. Alternatively, in someembodiments, the system or method may perform the transformation andquery iteratively, whereby the initial message is transformed using asubset of available transformation operations, the data store is queriedfor a second corresponding message based on the resulting transformedmessage, and if a second corresponding message is not identified,another iteration of transformation and query is performed (e.g., theresulting transformed message is further transformed using anothersubset available transformation operations, and the data store isqueried for a second corresponding message based on the resultingtransformed message). In some such embodiments, the subset oftransformation operations applied in each iteration may be applied tothe initial message or may be applied to the latest resultingtransformed message.

Eventually, the method may assist in translating the initial message orthe transformed message to a corresponding message in the secondlanguage. In some embodiments, the initial message may be translated tothe corresponding message when the first corresponding message for theinitial message is not in the data store and the transformation enginedoes not transform at least a portion of the initial message.Additionally, in various embodiments, the transformed message may betranslated to the corresponding message when: the first correspondingmessage for the initial message is not in the data store; thetransformation engine results in a transformed message that contains thetransformation of at least a portion of the initial message; and thedata store does not include the second corresponding message for thetransformed message.

Depending on the embodiment, transforming the portion of the initialmessage may comprise identifying a chatspeak word or phrase (e.g.,‘lol,’ ‘gr8t,’) in the initial message and replacing the chatspeak wordor phrase with a non-chatspeak word or phrase, performing a spellingcheck on the portion of the initial message, or identifying anabbreviation in the portion of the initial message and replacing theabbreviation with a word or a phrase corresponding to (e.g., representedby) the abbreviation (e.g., ‘CA’ with ‘California,’ or ‘brb’ to ‘beright back’).

In addition, transforming the portion of the initial message maycomprise identifying an acronym in the portion of the initial messageand replacing the acronym with a word or a phrase corresponding to(e.g., represented by) the acronym (e.g., ‘USA’), or identifying acolloquial word or phrase in the portion of the initial message andreplacing the colloquial word or phrase with a word or a phraserepresenting the colloquial word or phrase. Furthermore, transformingthe portion of the initial message may comprise identifying a profaneword or phrase in the portion of the initial message and replacing theprofane word or phrase with a non-profane word or a phrase (e.g., thatis representative of the profane word or phrase) or removing the profaneword or phrase from the initial message.

For some embodiments, transforming the portion of the initial messagecomprises flagging the portion of the initial message to not betranslated. For instance, wherein a certain portion of the initialmessage comprises a proper noun, a common noun, a diminutive, anabbreviation, or an acronym, the method may flag that certain portionsuch that it is not translated in subsequent operations.

Certain embodiments provide for a system comprising various componentsthat are configured to perform various operations described herein.Likewise, certain embodiments provides for a computer program productcomprising computer instruction codes configured to cause the computersystem to perform various operations described herein.

Other features and aspects of various embodiments will become apparentfrom the following detailed description, taken in conjunction with theaccompanying drawings, which illustrate, by way of example, the featuresof such embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments are described in detail with reference to thefollowing figures. The drawings are provided for purposes ofillustration only and merely depict some embodiments. These drawingsshall not be considered limiting of the breadth, scope, or applicabilityof embodiments.

FIG. 1 is a block diagram illustrating an exemplary environmentutilizing a multi-lingual communications system in accordance withvarious embodiments.

FIG. 2 is a block diagram illustrating an exemplary communicationtransformation and translation system in accordance with variousembodiments.

FIG. 3 is a block diagram illustrating an exemplary transformationmodule in accordance with various embodiments.

FIG. 4 is a block diagram illustrating an exemplary chat client systemin accordance with various embodiments.

FIG. 5 is a flowchart illustrating an exemplary method of multi-lingualcommunication in accordance with various embodiments.

FIG. 6 is a flowchart illustrating an exemplary method of transformingcommunications in accordance with various embodiments.

FIG. 7 is a diagram illustrating an exemplary multi-lingual chat sessionbetween chat client systems, in accordance with various embodiments.

FIG. 8 is a flowchart illustrating operation of an exemplarymulti-lingual communication method in accordance with variousembodiments.

FIG. 9 is a flowchart illustrating operation of an exemplarymulti-lingual communication method in accordance with variousembodiments.

FIG. 10 is a flowchart illustrating operation of an exemplarymulti-lingual communication method in accordance with variousembodiments.

FIG. 11 is a flowchart illustrating operation of an exemplarymulti-lingual communication method in accordance with variousembodiments.

FIG. 12 is a block diagram illustrating an exemplary digital device thatcan be utilized in the implementation of various embodiments.

DETAILED DESCRIPTION

Various embodiments described herein relate to and facilitatemulti-lingual communications. The systems and methods of someembodiments may enable multi-lingual communications through differentmodes of communications including, for example, Internet-based chat(e.g., Apple® iMessage, Windows® Live Messenger, etc.), e-mail (e.g.,embedded forum messaging, Yahoo® mail, RFC 5322, etc.), text-basedmobile phone communications (e.g., SMS messages or MMS messages),postings to online forums (e.g., postings to a web-based hobby forum),postings to online social media services (e.g., Twitter®, Facebook®,etc.), and the like. Certain embodiments may also be used to translatetranscripts of communications or conversations that took place in thepast (e.g., deposition transcripts or chat history). Various embodimentsmay implement communications systems and methods that translate textbetween two or more languages (e.g., spoken), whilehandling/accommodating for one or more of the following in the text:specialized/domain-related jargon (e.g., chatspeak), abbreviations,acronyms, proper nouns, common nouns, diminutives, colloquial words orphrases, and profane words or phrases. For example, some systems andmethods described herein may be utilized in connection with a chatsystem, such as those used in massive-multiplayer online (MMO) games,which tend to have users that chat in different foreign languages.Through certain embodiments, the chat dialogue between two or more userscan be transparently translated and presented to each user in theirrespective native language or language of choice. Additionally, throughthe use of a multi-tiered/multi-module transformation process, certainembodiments may facilitate faster translation of communication betweentwo or more users (e.g., in their respective native languages) thanotherwise possible by traditional translation systems alone (e.g.,translation in a matter of microseconds).

According to some embodiments, a system or method may performtranslation from chatspeak in a first language, such as English, tochatspeak in a second language, such as French. In another example, asystem or method may perform transformation from chatspeak in the firstlanguage (e.g., English) to formal speak in the first language (e.g.,English), before attempting translation to the second language (e.g.,French). Some embodiments may achieve such text translations by firstquerying a data store (e.g., translations cache), which may containtranslations manually entered by a human operator or translations basedon previously performed by a translation system (e.g., historicaltranslations performed by an embodiment). Embodiments may attempt totransform one or more portions of the text (e.g., process one or more ofthe following within the text: chatspeak, acronyms, abbreviations,proper nouns, common nouns, colloquialisms, and profanity) to make itmore suitable for accurate text translation. For example, certainembodiments may transform a given text to account for (current or past)idiomatic language use across different languages. Embodiments mayreattempt querying the data store after transformation of the portionsof the text. If this translation lookup reattempt fails, embodiments mayattempt to translate the text (which may have been transformed) using amachine translation service (e.g., third-party, cloud-based translationservice, such as Google® translate).

Embodiments may attempt to transform a translated piece of formal textto chatspeak in the new language (e.g., transform French formal speak toFrench chatspeak) to further refine the translation of the texteventually produced. Accordingly, certain embodiments facilitate chattranslation between chatspeak in a first language (e.g., English) tochatspeak in a second language (e.g., Russian, French, Spanish, Chinese,Hindi, etc.).

Some embodiments may help reduce or avoid the need for using machinetranslations (thereby reducing time, cost, and other overhead associatedwith machine translations), and may facilitate accurate translations oftext having minimal context or comprising short sentence structure.Where the machine translation is facilitated by a third-party service orover a secure network connection (e.g., Secure-Socket Layer [SSL]connection), the cost or overhead avoided by certain embodiments may besignificant.

As understood herein, “transformation” means manipulating a first textsegment, in a first language, to form a second text segment in the firstlanguage. The resulting second text segment may also be referred toherein as the “transformed text.” “Translation” will be understood tomean converting a text segment in a first language to a correspondingtext segment in a second language.

As also understood herein, a “transformed translation” means translationof a text segment (from a first language to a second language) that hasalready been transformed in accordance with embodiments described herein(e.g., transformed from chatspeak text in a first language to formaltext in the first language). An “untransformed translation” will beunderstood to mean a translation of a text segment (from a firstlanguage to a second language) before the text segment has beentransformed in accordance with embodiments described herein.

Various embodiments may implement different transformation/translationstrategies, with certain strategies being well suited for particulartranslation applications. For example, for particular chat systemapplications, the transformation strategy implemented may compriseapplying the following set of transformation-related modules in theorder listed: chatspeak module, acronym module, proper noun module,common noun module, colloquialism module, spelling check module,abbreviation module, and profanity module. Generally, thetransformation/translation strategy employed determines whichtransformation operations are performed, when the transformationoperations are performed in the overall translation process (e.g.,transformation performed before or after machine translation), or inwhat order the transformation operations are performed (e.g., precedenceor priority of transformation operations). Thetransformation/translation strategy may also determine what translationsare pre-populated into the data store (e.g., translations can be storedin a translation “cache” to speed up the overall process) and whentranslation caches are utilized in the overall translation process. Forcertain embodiments, the transformation/translation strategy employedmay be dynamically determined based on the conditions of the environmentin which the embodiments are used. For example, where a chat system isexperiencing a heavier load of users than usual, thetransformation/translation strategy may switch to one that lessens theprocessing burden of the chat system (e.g., relies more on machinetranslations rather than on the data store).

FIG. 1 is a block diagram illustrating an exemplary environment 100utilizing a multi-lingual system in accordance with various embodiments.As shown in FIG. 1, the exemplary environment 100 comprises clients102-1 through 102-N (hereafter, collectively referred to as “clients102” or “client 102”), a chat server 108, and a translation server 110,each of which may be communicatively coupled with each other through acomputer network 106. In accordance with some embodiments, the computernetwork 106 may be implemented or facilitated using one or more local orwide-area communications networks, such as the Internet, WiFi networks,WiMax networks, private networks, public networks, and the like.Depending on the embodiment, some or all of the communicationconnections with the computer network 106 may utilize encryption (e.g.,Secure Sockets Layer [SSL]) to secure information being transferredbetween the various entities shown in the exemplary environment 100.

Each of the clients 102, the chat server 108, and the translation server110 may be implemented using one or more digital devices, which may besimilar to the digital devices discussed later with respect to FIG. 12.For instance, the client 102-1 may be any form of computing devicecapable of receiving user input (e.g., configured for user interaction),capable of providing a client user interface that facilitatescommunications with one or more other clients (e.g., any of clients102-2 through 102-N), and capable of communicating with the chat server108 through the computer network 106. Such computing devices may includea mobile phone, a tablet computing device, a laptop, a desktop computer,personal digital assistant, a portable gaming unit, a wired gaming unit,a thin client, a set-top box, a portable multi-media player, or anyother type of network accessible user device known to those of skill inthe art. Further, one or more of the chat server 108 and the translationserver 110 may comprise of one or more servers, which may be operatingon or implemented using one or more cloud-based services (e.g.,System-as-a-Service [SaaS], Platform-as-a-Service [PaaS], orInfrastructure-as-a-Service [IaaS]).

The clients 102 may be configured to communicatively connect with thechat server 108, which provides or otherwise facilitates chat sessionsbetween the clients 102. Each of the clients 102-1 through 102-N maycomprise a chat client system (104-1 through 104-N, respectively) thatenables a user at each of the clients 102 to access to the chat sessionthrough the chat server 108. Additionally, depending on the embodiment,each of the chat client systems 104-1 through 104-N (hereafter,collectively referred to as “chat client systems 104” or “chat clientsystem 104”) may be implemented as a standalone chat application, as achat feature embedded in non-chat application (e.g., video game), orthrough a chat service accessible at the client through a web browser.Those skilled in the art will appreciate that for some embodiments thechat client systems 104 may be non-heterogeneous with respect to oneanother and still be capable of establishing a chat session betweenthem. The chat client systems 104 may be capable of receiving chat input(e.g., a chat message) from their respective users in a language (andcorresponding character set) selected by the user (e.g., based on usersettings or preferences), and transmitting the chat input to the chatserver 108 to be relayed to another user (e.g., another user at anotherchat client system). The chat client systems 104 may also be capable ofreceiving chat output (e.g., chat session dialogue) from the chat server108 (e.g., from another user at another chat client system), anddisplaying the received chat output in a language (and correspondingcharacter set) selected by the user (e.g., based on user settings orpreferences).

Through the use of some embodiments, the translation of the chatdialogue may be transparent to the users as dialogue is passed betweenthe chat client systems 104. Accordingly, for some embodiments, all chatdialogue presented at a given chat client system 104 may be in alanguage native to (or selected by) the user at that given chat clientsystem 104, irrespective of what language is being by users, at otherchat client systems 104 that are contributing to the same chat dialogue.For example, where the user at the chat client system 104-1 and the userat the chat client system 104-2 are contributing to the same chatdialogue (i.e., involved in the same chat session), the user at the chatclient system 104-1 may have chosen to enter and receive chat dialoguein English while the user at the chat client system 104-2 may havechosen to enter and receive chat dialogue in Russian. Though the usersat the client systems 104-1 and 104-2 will see the same chat content,the chat dialogue will be presented in their respectively chosenlanguages.

As shown, the chat server 108 may comprise a chat host system 112configured to established and/or facilitate chat sessions between thechat client systems 104, and a communication transformation andtranslation (CTT) system 114 configured to perform transformation and/ortranslation operations in accordance with the various systems andmethods described herein. For some embodiments, the chat client systems104 may establish a chat session with each other through the chat hostsystem 112, and the chat host system 104 may utilize the features of theCTT system 114 in facilitating the transparent translation of chatdialogue between the chat client systems 104. Those skilled in the artwill appreciate that for some embodiments, the chat host system 112 andthe CTT system 114 may be part of separate servers, and that the entityoperating the chat host system 112 may be different from the entityoperating the CTT system 114. For instance, the chat host system 112 maybe a third-party chat host system that utilizes the services of the CTTsystem 114.

As also shown, the translation server 110 may comprise a translationmodule 116 configured to receive and service requests for machine texttranslation. In accordance with some embodiments, the CTT system 114 mayutilize the operations/services of the translation module 116 inperforming machine translations of texts. The CTT system 114 may use ofone or more translation application programming interfaces (APIs) toobtain access to the services provided by the translation module 116.Depending on the embodiment, the translation module 116 (and the server110 on which it resides) may be operated by a third-party, such asGoogle®, which may offer the machine translation services free of chargeor for a fee. Though the translation module 116 is shown to be acomponent operating on a server separate from the CTT system 114, thoseskilled in the art will appreciate that, for some embodiments, thetranslation module 116 may operating on the same server as the CTTsystem 114 and/or may be an integrated component of the CTT system 114.

FIG. 2 is a block diagram illustrating an exemplary communicationtransformation and translation system 114 in accordance with variousembodiments. As shown, the CTT system 114 may comprise a communicationtransformation and translation (CTT) control module 202, a communicationtransformation and translation (CTT) communications module 204, alanguage module 206, a transformation module 208, a translation datastore 210, and a translation application programming interface (API)module 212. The CTT control module 202 may be configured to controland/or orchestrate performance of various operations within the CTTsystem 114 as the CTT system 114 performs transformation or translationoperations in accordance with some systems and methods described herein.For some embodiments, the CTT control module 202 may control theoperation of other components of the CTT system 114, such as the CTTcommunications module 204, the language module 206, the transformationmodule 208, the translation data stores 210, and the translation APImodule 212.

The CTT communications module 204 may be configured to facilitatecommunications between the CTT system 114 and systems and componentsexternal to the CTT system 114, such as the chat server 108 and/or thetranslation server 110. Accordingly, through the CTT communicationsmodule 204, the CTT system 114 may receive the chat dialogue (comprisingone or more chat messages) to be transformed or translated by the CTTsystem 114, and may output the translated chat dialogue that resultsfrom the CTT system 114.

The language module 206 may be configured to identify the one or morelanguages used in connection with chat dialogue received by the CTTsystem 114. For some embodiments, the language module 206 may identifythe language through analysis of the content of the chat dialoguereceived, and/or obtaining language preference/settings information fromthe respective chat client systems (e.g., chat client systems 104)involved with the chat dialogue received.

The transformation module 208 may be configured to performtransformation operations on chat dialogue (comprising one or more chatmessages), received by the CTT system 114, in accordance with somesystems and methods described herein. In accordance with someembodiments, the transformation operations performed by thetransformation module 208 may include, without limitation, thoserelating to chatspeak, acronyms, abbreviations, proper nouns, commonnouns, colloquialisms, and profanity. Additional details of thetransformation module 208 are discussed in FIG. 3.

The translation data store 210 may be configured to store andsubsequently provide previously translated text to the CTT system 114 asthe CTT system 114 performs transformed translations and untransformedtranslations in accordance with the some system and methods describedherein. As described herein, the translation data store 210 may operateas a cache for translations previously performed by the CTT system 114,and/or may store translations manually entered and stored by a humanoperator (e.g., by way of a translation training system). For someembodiments, the translation data store 210 may be populated withtranslations that would speed up the performance of the CTT system 114with respect to certain chat contexts. For example, where the CTT system114 is utilized in conjunction with a chat system associated with an MMOgame, the translation data store 210 may be populated (e.g., by theoperator of the CTT system 114) with (transformed and untransformed)translations relating specifically to the MMO game. For certainembodiments, the multi-tiered/multi-module approach of transforming textused by the transformation module 208 is particularly well suited forhandling chat text in MMO games, which by nature tends to be complex.

Depending on the embodiment, the data store 210 may store eitheruntransformed translations (e.g., <English Formal> ‘you’→<French Formal>‘vous’), transformed translations (e.g., <English Chatspeak> ‘u’→<FrenchFormal> ‘vous’), or both. For some embodiments, the translation datastore 210 may store translations such that corresponding chat messagesmay be identified using hash values/tags. For instance, to store aSpanish translation for an original message in English, the Spanishtranslation may be stored based on a hash value of the English message,thereby enabling the Spanish translation to be later located andobtained using the hash value of the English message. Those skilled inthe art will appreciate that for some embodiments, the translation datastore 210 may comprise a separate data store for translations betweentwo specific languages. Accordingly, when a chat message is beingtransformed/translated between English and French, a corresponding dataEnglish-French data store may be utilized for operations relating to thetranslation data store 210.

The translation API module 212 may be configured to provide the CTTsystem 114 with access to machine translation services provided externalto the CTT system 114 (e.g., by the translation module 116 of thetranslation server 110). As described herein, the translation API module212 may be utilized by the CTT system 114 when a translation is notlocated in the translation data store 210.

FIG. 3 is a block diagram illustrating an exemplary transformationmodule 208 in accordance with various embodiments. As shown, thetransformation module 208 may comprise a chatspeak module 302, anacronym module 304, a proper noun module 306, a common noun module 308,a colloquialism module 310, a spelling check module 312, an abbreviationmodule 314, and/or a profanity module 316. According to someembodiments, during operation the transformation module 208 may processa chat message in whole or in parts (e.g., breaks the message intotokens or logical portions and then processes those tokens/portions). Insome embodiments, various modules of the transformation module 208 maybe called in parallel.

The chatspeak module 302 may be configured to identify one or more wordsor phrases in a chat message that are associated with chat jargon (i.e.,chatspeak), and may be further configured to suggest replacement (e.g.,corresponding formal/i.e., non-chatspeak) words or phrases for theidentified words or phrases. In some embodiments, the chatspeak module302 may flag an identified chatspeak word or phrase to be skipped orotherwise ignored during a subsequent machine translation (e.g., by thetranslation module 116). Additionally, in some embodiments, anidentified chatspeak word or phrase may be flagged for later review anddisposition by a human operator (e.g., an administrator of the CTTsystem 114). In order to identify a chatspeak word or phrase and/or itscorresponding (formal) word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising chatspeak words orphrases and/or mappings between chatspeak words or phrases and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. For example, the chatspeak module 302 may employstatistical machine translation in its functionality. For someembodiments, the statistical machine translation employed may be trainedusing parallel texts and/or using phrase-level pairs extracted fromtransformations that preserve contextual information and/or add grammarto an otherwise ungrammatical sentence. The result from the chatspeakmodule 302 may comprise a chatspeak word or phrase flagged by thechatspeak module 302 to be ignored, a suggested replacement, or anon-chatspeak word or phrase inserted into the message by the chatspeakmodule 302 (e.g., in place of the identified chatspeak word or phrase).Depending on the embodiment, the message that results from the chatspeakmodule 302 may be provided to another transformation module (in thetransformation module 208) for further processing or the suggestedreplacement may be provided to the CTT control module 202 to determineif the message transformed by the chatspeak module 302 is in the datastore 210.

The acronym module 304 may be configured to identify one or moreacronyms in a chat message, and may be further configured to suggestreplacement words or phrases corresponding to (e.g., represented by) theacronyms. In some embodiments, the acronym module 304 may flag anidentified acronym to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified acronym may be flaggedfor later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify an acronymand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising acronyms and/ormappings between acronyms and their corresponding words and phrases. Thedataset may be constructed by way of training or a learning system, maybe proprietary (e.g., manually collected “in-house” by an administratorof the CTT system 114), may be commercially acquired, or may be derivedfrom a publicly available Internet knowledgebase. The result from theacronym module 304 may comprise an acronym flagged by the acronym module304 to be ignored, a suggested replacement, or a word or phrase insertedinto the message by the acronym module 304 (e.g., in place of theidentified acronym). Depending on the embodiment, the message thatresults from the acronym module 304 may be provided to anothertransformation module (in the transformation module 208) for furtherprocessing or the suggested replacement may be provided to the CTTcontrol module 202 to determine if the message transformed by theacronym module 304 is in the data store 210.

The proper noun module 306 may be configured to identify one or moreproper nouns in a chat message, and may be further configured to suggestreplacement words or phrases corresponding to (e.g., represented by) theproper nouns. In some embodiments, the proper noun module 306 may flagan identified proper noun to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified proper noun may beflagged for later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify a proper nounand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising proper nouns (e.g.,well-known proper nouns such as Disneyland®, or common names forindividuals) and/or mappings between proper nouns and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The result from the proper noun module 306 maycomprise a proper noun flagged by the proper noun module 306 to beignored, a suggested replacement, or a word or phrase inserted into themessage by the proper noun module 306 (e.g., in place of the identifiedproper noun). Depending on the embodiment, the message that results fromthe proper noun module 306 may be provided to another transformationmodule (in the transformation module 208) for further processing or thesuggested replacement may be provided to the CTT control module 202 todetermine if the message transformed by the proper noun module 306 is inthe data store 210.

The common noun module 308 may be configured to identify one or morecommon nouns in a chat message, and may be further configured to suggestreplacement words or phrases corresponding to (e.g., represented by) thecommon nouns. In some embodiments, the common noun module 308 may flagan identified common noun to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified common noun may beflagged for later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify a common nounand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising common nouns and/ormappings between common nouns and their corresponding words and phrases.The dataset may be constructed by way of training or a learning system,may be proprietary (e.g., manually collected “in-house” by anadministrator of the CTT system 114), may be commercially acquired, ormay be derived from a publicly available Internet knowledgebase. Theresult from the common noun module 308 may comprise a common nounflagged by the common noun module 308 to be ignored, a suggestedreplacement, or a word or phrase inserted into the message by the commonnoun module 308 (e.g., in place of the identified common noun).Depending on the embodiment, the message that results from the commonnoun module 308 may be provided to another transformation module (in thetransformation module 208) for further processing or the suggestedreplacement may be provided to the CTT control module 202 to determineif the message transformed by the common noun module 308 is in the datastore 210.

The colloquialism module 310 may be configured to identify one or morecolloquial words or phrases in a chat message, and may be furtherconfigured to suggest replacement (e.g., corresponding formal/i.e.,non-colloquial) words or phrases for the identified words or phrases. Insome embodiments, the colloquialism module 310 may flag an identifiedcolloquial word or phrase to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified colloquial word orphrase may be flagged for later review and disposition by a humanoperator (e.g., an administrator of the CTT system 114). In order toidentify a colloquial word or phrase and/or its corresponding (formal)word or phrase, some embodiments may utilize a dataset (e.g., stored ona data store) comprising colloquial words or phrases and/or mappingsbetween colloquial words or phrases and their corresponding words andphrases. The dataset may be constructed by way of training or a learningsystem, may be proprietary (e.g., manually collected “in-house” by anadministrator of the CTT system 114), may be commercially acquired, ormay be derived from a publicly available Internet knowledgebase. Theresult from the colloquialism module 310 may comprise a colloquial wordor phrase flagged by the colloquialism module 310 to be ignored, asuggested replacement, or a non-colloquial word or phrase inserted intothe message by the colloquialism module 310 (e.g., in place of theidentified colloquial word or phrase). Depending on the embodiment, themessage that results from the colloquialism module 310 may be providedto another transformation module (in the transformation module 208) forfurther processing or the suggested replacement may be provided to theCTT control module 202 to determine if the message transformed by thecolloquialism module 310 is in the data store 210.

The spelling check module 312 may be configured to identify one or moremisspelled words or phrases in a chat message, and may be furtherconfigured to suggest replacement (e.g. corrected) words or phrases forthe identified words or phrases. For example, the spelling check module312 may be configured to automatically correct the words or phrases withthe suggested replacement words or phrases. In some embodiments, thespelling check module 312 may flag an identified misspelled word orphrase to be skipped or otherwise ignored during a subsequent machinetranslation (e.g., by the translation module 116). Additionally, in someembodiments, an identified misspelled word or phrase may be flagged forlater review and disposition by a human operator (e.g., an administratorof the CTT system 114). In order to identify a misspelled word or phraseand/or its corresponding (corrected) word or phrase, some embodimentsmay utilize a dataset (e.g., stored on a data store) comprisingmisspelled words or phrases and/or mappings between misspelled words orphrases and their corresponding words and phrases. The dataset may beconstructed by way of training or a learning system, may be proprietary(e.g., manually collected “in-house” by an administrator of the CTTsystem 114), may be commercially acquired, or may be derived from apublicly available Internet knowledgebase. The result from the spellingcheck module 312 may comprise a misspelled word or phrase flagged by thespelling check module 312 to be ignored, a suggested replacement, or acorrected word or phrase inserted into the message by the spelling checkmodule 312 (e.g., in place of the misspelled word or phrase). Dependingon the embodiment, the message that results from the spelling checkmodule 312 may be provided to another transformation module (in thetransformation module 208) for further processing or the suggestedreplacement may be provided to the CTT control module 202 to determineif the message transformed by the spelling check module 312 is in thedata store 210.

The abbreviation module 314 may be configured to identify one or moreabbreviations in a chat message, and may be further configured tosuggest replacement words or phrases corresponding to (e.g., representedby) the abbreviations. In some embodiments, the abbreviation module 314may flag an identified abbreviation to be skipped or otherwise ignoredduring a subsequent machine translation (e.g., by the translation module116). Additionally, in some embodiments, an identified abbreviation maybe flagged for later review and disposition by a human operator (e.g.,an administrator of the CTT system 114). In order to identify anabbreviation and/or its corresponding word or phrase, some embodimentsmay utilize a dataset (e.g., stored on a data store) comprisingabbreviations and/or mappings between abbreviations and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The result from the abbreviation module 314 maycomprise an abbreviation flagged by the abbreviation module 314 to beignored, a suggested replacement, or a word or phrase inserted into themessage by the abbreviation module 314 (e.g., in place of the identifiedabbreviation). Depending on the embodiment, the message that resultsfrom the abbreviation module 314 may be provided to anothertransformation module (in the transformation module 208) for furtherprocessing or the suggested replacement may be provided to the CTTcontrol module 202 to determine if the message transformed by theabbreviation module 314 is in the data store 210.

The profanity module 316 may be configured to identify one or moreprofane words or phrases (hereafter, referred to as a “profanity”) in achat message, and may be further configured to suggest replacement wordsor phrases (e.g., suitable substitute) corresponding to the profanity(e.g., a toned down euphemism). In some embodiments, the profanitymodule 316 may flag identified profanity to be skipped or otherwiseignored during a subsequent machine translation (e.g., by thetranslation module 116). Additionally, in some embodiments, identifiedprofanity may be flagged for later review and disposition by a humanoperator (e.g., an administrator of the CTT system 114). In order toidentify profanity and/or its corresponding word or phrase, someembodiments may utilize a dataset (e.g., stored on a data store)comprising profanity and/or mappings between abbreviations and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The result from the profanity module 316 maycomprise profanity flagged by the profanity module 316 to be ignored, asuggested replacement, or a word or phrase inserted into the message bythe profanity module 316 (e.g., in place of the identified profanity).Depending on the embodiment, the message that results from the profanitymodule 316 may be provided to another transformation module (in thetransformation module 208) for further processing or the suggestedreplacement may be provided to the CTT control module 202 to determineif the message transformed by the profanity module 316 is in the datastore 210.

For some embodiments, one or more various modules of the transformationmodule 208 may flag one or more portions of the chat message byinserting a predetermined character before and/or after the portionbeing flagged. For instance, where the chatspeak module 302 flags theword “LOL” in a portion of the chat message, the chatspeak module 302may insert an predetermined character (“_”) before and/or after the word(e.g., “_LOL_”) to indicate that the flagged portion should be ignoredby the translation module 116.

For some embodiments, the transformation module 208 may perform two ormore transformation operations on the initial message in parallel, andin response, each of the two or more transformation operations mayreturn a separate response, from which the transformation module 208 maythen select one transformed message for further processing (e.g., to beused in operation 514). Depending on the embodiment, each response maycomprise a flagged text portion, a suggested replacement, or a word orphrase inserted into the initial message. Thereafter, the transformedmessage selected may be according to a priority of selection, which candetermine which transformed message is selected for further processingand according to what precedent. In some embodiments, the priorityselection may be according to which transformation operation is mostlikely to generate a transformed message suitable for a subsequentlookup in the translation data store 210) or for subsequent machinetranslation. Additionally, in some embodiments, the priority ofselection may be according to which transformation operation generatesthe most formal transformed message. The priority of selection maydepend on the transformation/translation strategy selected by theembodiment.

The following provides examples of how the transformation module 208 mayprocess a portion of a chat message in accordance with variousembodiments. As shown, the transformation module 208 may process a chatmessage based on tokens or proximal tokens, and may cease processing ona particular token once a transformation is performed.

Token(s) from a Chat Message Transformation Processing Token = ‘USA’Chatspeak Module (‘USA’) → Acronym Module (‘USA’) → Flag fornon-translation. Token = ‘brb’ Chatspeak Module (‘brb’) → Acronym Module(‘brb’) → Proper Noun Module (‘brb’) → Common Noun Module (‘brb’) →Colloquialism Module (‘brb’) → Spelling Check Module(‘brb’) →Abbreviation Module (‘brb’) →Transform to ‘be right back’ Token = ‘9’Chatspeak Module (‘9’) →Transform to ‘parents watching over shoulder’Token = ‘99’ Chatspeak Module (‘99’) →Transform to ‘parents stoppedwatching over shoulder’ Proximal tokens = Chatspeak Module (‘go gabe’) →Acronym ‘go gabe’ Module (‘go gabe’) → Proper Noun Module (‘going’) →Common Noun Module (‘go gabe’) → Flag for likely being a common noun.String = ‘Your going Spelling Check Module (‘Your’) → Correct to attackhim?’ with ‘You're’ based on proximal token ‘going’ Token#1 = ‘Your’(i.e., using proximal context for spell Token#2 = ‘going’ checking).Token#3 = ‘to’ Chatspeak Module (‘going’) → Acronym Token#4 = ‘attack’Module (‘going’) → Proper Noun Module Token#5 = ‘him’ (‘going’) → CommonNoun Module (‘going’) → Colloquialism Module (‘going’) → Spelling CheckModule(‘going’) → Abbreviation Module (‘going’) → Profanity Module(‘going’) → No transform. Chatspeak Module (‘to’) → Acronym Module(‘to’) → Proper Noun Module (‘to’) → Common Noun Module (‘to’) →Colloquialism Module (‘to’) → Spelling Check Module(‘to’) → AbbreviationModule (‘to’) → Profanity Module (‘to’) → No transform. Chatspeak Module(‘attack’) → Acronym Module (‘attack’) → Proper Noun Module (‘attack’) →Common Noun Module (‘attack’) → Colloquialism Module (‘attack’) →Spelling Check Module(‘attack’) → Abbreviation Module (‘attack’) →Profanity Module (‘attack’) → No transform. Chatspeak Module (‘him’) →Acronym Module (‘him’) → Proper Noun Module (‘him’) → Common Noun Module(‘him’) → Colloquialism Module (‘him’) → Spelling Check Module(‘him’) →Abbreviation Module (‘him’) → Profanity Module (‘him’) → No transform.String = ‘Sup bro, Chatspeak Module (‘Sup’) → Replace with sup yall?’“How is it going.” Token#1 = ‘Sup’ Chatspeak Module (‘bro’) → AcronymToken#2 = ‘bro’ Module (‘bro’) → Proper Noun Module (‘bro’) Token#3 =‘sup’ → Common Noun Module (‘bro’) → Token#4 = ‘yall’ ColloquialismModule (‘bro’) → Spelling Check Module(‘bro’) → Abbreviation Module(‘bro’) → Replace with “brother” Chatspeak Module (‘sup’) → Replace with“how is it going.” Chatspeak Module (‘yall’) → Replace with “you all.”

FIG. 4 is a block diagram illustrating an exemplary chat client system104 in accordance with various embodiments. As shown, the chat clientsystem 104 may comprise a chat client controller 402, a chat clientcommunications module 404, and a chat client graphical user interface(GUI) module 406. The chat client control module 402 may be configuredto control and/or orchestrate performance of various operations withinthe chat client system 104 as the chat client system 104 performs chatrelated operations (e.g., communications chat dialogue with the chatserver 108). For some embodiments, the chat client control module 402may control the operation of other components of the chat client system104 including, for example, such as the chat client communicationsmodule 404, and the chat client GUI module 406.

The chat client communications module 404 may be configured tofacilitate communications between the chat client system 104 and systemsand components external to the chat client system 104, such as the chatserver 108. Accordingly, through the chat client module 404, the chatclient system 104 may receive from the chat server 108 the chat dialogueto be presented at the chat client system 104 (e.g., via the chat clientGUI module 406), and may send to the chat server the chat dialoguereceived from the user at the chat client system 104 (e.g., via the chatclient GUI module 406).

The chat client GUI module 406 may be configured to provide a user atthe chat client system 104 with graphical input/output access to chatsessions with other chat client systems. Accordingly, for someembodiments the chat client GUI module 406 may present a user at theclient 102 with a client GUI adapted for receiving user interactionsthrough the client 102. For some embodiments, the chat client GUI module406 may be configured to present the user with chat dialogue (e.g., asthey are received from the chat server 108) in the language of theirchoice (e.g., according to the user language preferences/settings).Additionally, the chat client GUI module 406 may be configured toreceive chat input from the user in the language of their choice (e.g.,according to the user language preferences/settings). As describedherein, the language used in presenting and receiving the chat dialogueat the chat client system 104 may be different from the language used inpresenting and receiving the chat dialogue at another chat clientsystem. More regarding the chat client GUI module 406 is discussed withrespect to FIG. 7.

FIG. 5 is a flowchart illustrating an exemplary method 500 formulti-lingual communication in accordance with various embodiments. Asdescribed below, for some embodiments, the method illustrated by themethod 500 may perform operations in connection with the chat clientsystem 104-1, the chat client system 104-2, the CTT system 114 (e.g., ofthe chat server 108), and the translation module 116 (e.g., oftranslation server 110).

The method 500 may start at operation 502, the language module 204 (ofthe CTT system 114) may being by identifying a first language being usedby a user at a first chat client system (e.g., 104-1) and a secondlanguage being used by a user at a second chat client system (e.g.,104-2). According to some embodiments, the language module 204 mayidentify the first language and the second language by obtaininglanguage preferences/settings from the respective chat client system104.

At operation 504, the CTT communications module 204 (of the CTT system114) may receive an initial message in the first language. In someembodiments, the CTT communications module 204 may receive the initialmessage from the chat host system 112, which may have received theinitial message from a chat client system (e.g., 104-1).

At operation 506, the CTT control module 202 (of the CTT system 114) mayquery the translation data store 210 for a corresponding message in thesecond language that corresponds to the initial message. At operation508, the CTT control module 202 may determine if a corresponding messageis found in the translation data store 210. If one exists, at operation510, the CTT communications module 204 may assist in sending thecorresponding message to the second chat client system (e.g., the chatclient system 104-2). In some embodiments, the corresponding message maybe sent to the chat host system 112, which may relay the correspondingmessage to the second chat client system (e.g., 104-2). The method 500may then end.

If a corresponding message does not exist in the translation data store210, at operation 512, the transformation module 208 may attempt totransform at least a portion of the initial message to a transformedmessage in the first language. As described herein, the message thatresults from the transformation module 208 may be transformed or mayremain unchanged (e.g., when transformation operations of thetransformation module 208 are not applied to the initial message). Forsome embodiments, the transformation module 208 may perform two or moretransformation operations on the initial message in parallel, and inresponse, each of the two or more transformation operations may return aseparate response, from which the transformation module 208 may thenselect one transformed message for further processing (e.g., to be usedin operation 514). Depending on the embodiment, each response maycomprise a flagged text portion, a suggested replacement, or a word orphrase inserted into the initial message. Thereafter, the transformedmessage selected may be according to a priority of selection, which candetermine which transformed message is selected for further processingand according to what precedent. In some embodiments, the priorityselection may be according to which transformation operation is mostlikely to generate a transformed message suitable for a subsequentlookup in the translation data store 210) or for subsequent machinetranslation. Additionally, in some embodiments, the priority ofselection may be according to which transformation operation generatesthe most formal transformed message. The priority of selection maydepend on the transformation/translation strategy selected by theembodiment.

At operation 514, assuming the transformation module 208 transformed themessage, the CTT control module 202 (of the CTT system 114) may querythe translation data store 210 for a corresponding message in the secondlanguage that corresponds to the transformed message. At operation 516,the CTT control module 202 may determine if a corresponding message isfound in the translation data store 210. If one exists, at operation518, the CTT communications module 204 may assist in sending thecorresponding message to the second chat client system (e.g., the chatclient system 104-2). In some embodiments, the corresponding message maybe sent to the chat host system 112, which may then relay thecorresponding message to the second chat client system (e.g., 104-2).The method 500 may then end.

For some embodiments, if a corresponding message still does not exist inthe translation data store 210, at operation 520, the CTT control module202 may determine if there are any additional transformation operationsof the transformation module 208 to perform on the chat message thathave not already been performed.

If an additional transformation operation exists, the method 500 returnsto operation 512 and performs additional transformation operation(s).Depending on the embodiment, the additional transformation operation(s)may involve applying a transform operation different from those alreadyperformed on the initial message by the transformation module 208, mayinvolve applying the same transformation operations performed but todifferent portions of the English chat message, or may involve somecombination thereof. For example, if during the first execution ofoperation 512 the transformation module 208 applies a chatspeak-relatedoperation to the initial message (to create a first transformedmessage), during a second execution of operation 512 the transformationmodule 208 may apply an abbreviation-related operation to the secondtransformed message. Following, a subsequent execution of operation 512,the method 500 may continue to operations 514 and 516, where the CTTcontrol module 202 may re-query the translation data store 210 for acorresponding message in the second language that corresponds to thelatest resulting transformed message, and the CTT control module 202 maydetermine if a corresponding message is found in the translation datastore 210. By performing the transformation and query operations in thisiterative manner, certain embodiments may be able to find acorresponding message before having to perform every transformationoperation available. Those skilled in the art will appreciate that forcertain embodiments, the transformation and query operations may beperformed in series, with the query operation (e.g., operation 514) onlybeing performed after every available transformation operation providedby the transformation module 208 has been performed on the chat message.

If a corresponding message does not exist in the translation data store210 and an additional transformation operation (of the transformationmodule 208) does not exist, at operation 522, (through the translationAPI module 212) the translation module 116 may assist in the translatingthe initial message or the transformed message to a correspondingmessage in the second language. Subsequently, at operation 524, the CTTcommunications module 204 may assist in sending the correspondingmessage to the second chat client system (e.g., the chat client system104-2). According to some embodiments, the corresponding message may besent to the chat host system 112, which may then relay the correspondingmessage to the second chat client system (e.g., 104-2). The method 500may then end.

For certain embodiments, the transformation module 208 may be utilizedto transform the corresponding message in the second language before thecorresponding message is sent to the chat host system 112. As describedherein, the corresponding message may be submitted for furthertransformation processing to further refine the translation for the userat the second chat client system (e.g., 104-2). For example, if theinitial message contains chatspeak in the first language (e.g.,English), additional transformation processing can add, to the extentpossible, chatspeak in the second language.

Though the steps of the above method may be depicted and described in acertain order, those skilled in the art will appreciate that the orderin which the steps are performed may vary between embodiments.Additionally, those skilled in the art will appreciate that thecomponents described above with respect to the method 500 are merelyexamples of components that may be used with the method, and for someembodiments other components may also be utilized in some embodiments.

FIG. 6 is a flowchart illustrating an exemplary method 600 fortransforming communications in accordance with various embodiments. Asdescribed below, for some embodiments, the method 600 may performoperations in connection the transformation module 208 (e.g., of the CTTsystem 114).

The method may start at operation 602, with an initial message beingreceived by the transformation module 208 for transformation processing.Based on some embodiments, the transformation module 208 may receive theinitial message for transformation subsequent to a failure to identify amessage in the translation data store 210, and possibly before theinitial message is machine translated by a third-party or proprietarytranslation process (e.g., the translation module 116, which may beoffered as a cloud-based service). As described herein, thetransformation module 208 may be used in various embodiments tofacilitate or otherwise improve text translation, particularly where thetext comprises a minimal context, brief sentence construction,specialized/domain-related jargon (e.g., chatspeak for Internet-basedchat) abbreviations, acronyms, colloquialisms, proper nouns, commonnouns, profanity, or some combination thereof. Text translations thatmay benefit from the operations of the transformation module 208 mayinclude, without limitation, translations of texts originating fromconversations (e.g., transcript), from offline or online Internet-basedchat (e.g., instant messaging), and from mobile phone messaging (e.g.,SMS or MMS).

At operation 604, the chatspeak module 302 may identify one or morewords or phrases in the initial message that are associated with chatjargon (i.e., chatspeak), and may further suggest replacement (e.g.,corresponding formal/i.e., non-chatspeak) words or phrases for theidentified words or phrases. In some embodiments, the chatspeak module302 may flag an identified chatspeak word or phrase to be skipped orotherwise ignored during a subsequent machine translation (e.g., by thetranslation module 116). Additionally, in some embodiments, anidentified chatspeak word or phrase may be flagged for later review anddisposition by a human operator (e.g., an administrator of the CTTsystem 114). In order to identify a chatspeak word or phrase and/or itscorresponding (formal) word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising chatspeak words orphrases and/or mappings between chatspeak words or phrases and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 604(hereafter, “the first intermediate message”) may comprise a chatspeakword or phrase flagged by the chatspeak module 302 to be ignored, asuggested replacement, or a non-chatspeak word or phrase inserted intothe initial message by the chatspeak module 302 (e.g., in place of theidentified chatspeak word or phrase). In some instances, the firstintermediate message may be the same as the initial message (e.g., whenno replacement is performed by the chatspeak module 302). Depending onthe embodiment, the first intermediate message that results from thechatspeak module 302 may be provided to another transformation module(in the transformation module 208) for further processing or thesuggested replacement may be provided to the CTT control module 202 todetermine if the message transformed by the chatspeak module 302 is inthe data store 210. Following operation 604, the first intermediatemessage may be provided to the next operation (e.g., operation 606) ofthe transformation module 208 for processing.

At operation 606, the acronym module 304 may identify one or moreacronyms in a chat message, and may further suggest replacement words orphrases corresponding to (e.g., represented by) the acronyms. In someembodiments, the acronym module 304 may flag an identified acronym to beskipped or otherwise ignored during a subsequent machine translation(e.g., by the translation module 116). Additionally, in someembodiments, an identified acronym may be flagged for later review anddisposition by a human operator (e.g., an administrator of the CTTsystem 114). In order to identify an acronym and/or its correspondingword or phrase, some embodiments may utilize a dataset (e.g., stored ona data store) comprising acronyms and/or mappings between acronyms andtheir corresponding words and phrases. The dataset may be constructed byway of training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 606(hereafter, “the second intermediate message”) may comprise an acronymflagged by the acronym module 304 to be ignored, a suggestedreplacement, or a word or phrase inserted into the message by theacronym module 304 (e.g., in place of the identified acronym). In someinstances, the second intermediate message may be the same as the firstintermediate message (e.g., when no replacement is performed by theacronym module 304). Depending on the embodiment, the secondintermediate message that results from the acronym module 304 may beprovided to another transformation module (in the transformation module208) for further processing or the suggested replacement may be providedto the CTT control module 202 to determine if the message transformed bythe acronym module 304 is in the data store 210. Following operation606, the second intermediate message may be provided to the nextoperation (e.g., operation 608) of the transformation module 208 forprocessing.

At operation 608, the proper noun module 306 may identify one or moreproper nouns in a chat message, and may further suggest replacementwords or phrases corresponding to (e.g., represented by) the propernouns. In some embodiments, the proper noun module 306 may flag anidentified proper noun to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified proper noun may beflagged for later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify a proper nounand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising proper nouns (e.g.,well-known proper nouns such as Disneyland®, or common names forindividuals) and/or mappings between proper nouns and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 608(hereafter, “the third intermediate message”) may comprise a proper nounflagged by the proper noun module 306 to be ignored, a suggestedreplacement, or a word or phrase inserted into the message by the propernoun module 306 (e.g., in place of the identified proper noun). In someinstances, the third intermediate message may be the same as the secondintermediate message (e.g., when no replacement is performed by theproper noun module 306). Depending on the embodiment, the thirdintermediate message that results from the proper noun module 306 may beprovided to another transformation module (in the transformation module208) for further processing or the suggested replacement may be providedto the CTT control module 202 to determine if the message transformed bythe proper noun module 306 is in the data store 210. Following operation608, the third intermediate message may be provided to the nextoperation (e.g., operation 610) of the transformation module 208 forprocessing.

At operation 610, the common noun module 308 may identify one or morecommon nouns in a chat message, and may further suggest replacementwords or phrases corresponding to (e.g., represented by) the commonnouns. In some embodiments, the common noun module 308 may flag anidentified common noun to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified common noun may beflagged for later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify a common nounand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising common nouns and/ormappings between common nouns and their corresponding words and phrases.The dataset may be constructed by way of training or a learning system,may be proprietary (e.g., manually collected “in-house” by anadministrator of the CTT system 114), may be commercially acquired, ormay be derived from a publicly available Internet knowledgebase. Themessage resulting from operation 610 (hereafter, “the fourthintermediate message”) may comprise a common noun flagged by the commonnoun module 308 to be ignored, a suggested replacement, or a word orphrase inserted into the message by the common noun module 308 (e.g., inplace of the identified common noun). In some instances, the fourthintermediate message may be the same as the third intermediate message(e.g., when no replacement is performed by the common noun module 308).Depending on the embodiment, the fourth intermediate message thatresults from the common noun module 308 may be provided to anothertransformation module (in the transformation module 208) for furtherprocessing or the suggested replacement may be provided to the CTTcontrol module 202 to determine if the message transformed by the commonnoun module 308 is in the data store 210. Following operation 610, thefourth intermediate message may be provided to the next operation (e.g.,operation 612) of the transformation module 208 for processing.

At operation 612, the colloquialism module 310 may identify one or morecolloquial words or phrases in a chat message, and may further suggestreplacement (e.g., corresponding formal/i.e., non-colloquial) words orphrases for the identified words or phrases. In some embodiments, thecolloquialism module 310 may flag an identified colloquial word orphrase to be skipped or otherwise ignored during a subsequent machinetranslation (e.g., by the translation module 116). Additionally, in someembodiments, an identified colloquial word or phrase may be flagged forlater review and disposition by a human operator (e.g., an administratorof the CTT system 114). In order to identify a colloquial word or phraseand/or its corresponding (formal) word or phrase, some embodiments mayutilize a dataset (e.g., stored on a data store) comprising colloquialwords or phrases and/or mappings between colloquial words or phrases andtheir corresponding words and phrases. The dataset may be constructed byway of training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 612(hereafter, “the fifth intermediate message”) may comprise a colloquialword or phrase flagged by the colloquialism module 310 to be ignored, asuggested replacement, or a non-colloquial word or phrase inserted intothe message by the colloquialism module 310 (e.g., in place of theidentified colloquial word or phrase). In some instances, the fifthintermediate message may be the same as the fourth intermediate message(e.g., when no replacement is performed by the colloquialism noun module310). Depending on the embodiment, the fifth intermediate message thatresults from the colloquialism module 310 may be provided to anothertransformation module (in the transformation module 208) for furtherprocessing or the suggested replacement may be provided to the CTTcontrol module 202 to determine if the message transformed by thecolloquialism module 310 is in the data store 210. Following operation612, the fifth intermediate message may be provided to the nextoperation (e.g., operation 614) of the transformation module 208 forprocessing.

At operation 614, the spelling check module 312 may identify one or moremisspelled words or phrases in a chat message, and may further suggestreplacement (e.g. corrected) words or phrases for the identified wordsor phrases. For example, the spelling check module 312 may automaticallycorrect the words or phrases with the suggested replacement words orphrases. In some embodiments, the spelling check module 312 may flag anidentified misspelled word or phrase to be skipped or otherwise ignoredduring a subsequent machine translation (e.g., by the translation module116). Additionally, in some embodiments, an identified misspelled wordor phrase may be flagged for later review and disposition by a humanoperator (e.g., an administrator of the CTT system 114). In order toidentify a misspelled word or phrase and/or its corresponding(corrected) word or phrase, some embodiments may utilize a dataset(e.g., stored on a data store) comprising misspelled words or phrasesand/or mappings between misspelled words or phrases and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 614(hereafter, “the sixth intermediate message”) may comprise a misspelledword or phrase flagged by the spelling check module 312 to be ignored, asuggested replacement, or a corrected word or phrase inserted into themessage by the spelling check module 312 (e.g., in place of themisspelled word or phrase). In some instances, the sixth intermediatemessage may be the same as the fifth intermediate message (e.g., when noreplacement is performed by the spelling check module 312). Depending onthe embodiment, the sixth intermediate message that results from thespelling check module 312 may be provided to another transformationmodule (in the transformation module 208) for further processing or thesuggested replacement may be provided to the CTT control module 202 todetermine if the message transformed by the spelling check module 312 isin the data store 210. Following operation 614, the sixth intermediatemessage may be provided to the next operation (e.g., operation 616) ofthe transformation module 208 for processing.

At operation 616, the abbreviation module 314 may identify one or moreabbreviations in a chat message, and may further suggest replacementwords or phrases corresponding to (e.g., represented by) theabbreviations. In some embodiments, the abbreviation module 314 may flagan identified abbreviation to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, an identified abbreviation may beflagged for later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify anabbreviation and/or its corresponding word or phrase, some embodimentsmay utilize a dataset (e.g., stored on a data store) comprisingabbreviations and/or mappings between abbreviations and theircorresponding words and phrases. The dataset may be constructed by wayof training or a learning system, may be proprietary (e.g., manuallycollected “in-house” by an administrator of the CTT system 114), may becommercially acquired, or may be derived from a publicly availableInternet knowledgebase. The message resulting from operation 616(hereafter, “the seventh intermediate message”) may comprise anabbreviation flagged by the abbreviation module 314 to be ignored, asuggested replacement, or a word or phrase inserted into the message bythe abbreviation module 314 (e.g., in place of the identifiedabbreviation). In some instances, the seventh intermediate message maybe the same as the sixth intermediate message (e.g., when no replacementis performed by the abbreviation module 314). Depending on theembodiment, the seventh intermediate message that results from theabbreviation module 314 may be provided to another transformation module(in the transformation module 208) for further processing or thesuggested replacement may be provided to the CTT control module 202 todetermine if the message transformed by the abbreviation module 314 isin the data store 210. Following operation 616, the seventh intermediatemessage may be provided to the next operation (e.g., operation 618) ofthe transformation module 208 for processing.

At operation 618, the profanity module 316 may identify one or moreprofane words or phrases (hereafter, referred to as a “profanity”) in achat message, and may further suggest replacement words or phrases(e.g., suitable substitute) corresponding to the profanity (e.g., atoned down euphemism). In some embodiments, the profanity module 316 mayflag identified profanity to be skipped or otherwise ignored during asubsequent machine translation (e.g., by the translation module 116).Additionally, in some embodiments, identified profanity may be flaggedfor later review and disposition by a human operator (e.g., anadministrator of the CTT system 114). In order to identify profanityand/or its corresponding word or phrase, some embodiments may utilize adataset (e.g., stored on a data store) comprising profanity and/ormappings between abbreviations and their corresponding words andphrases. The dataset may be constructed by way of training or a learningsystem, may be proprietary (e.g., manually collected “in-house” by anadministrator of the CTT system 114), may be commercially acquired, ormay be derived from a publicly available Internet knowledgebase. Themessage resulting from operation 618 (hereafter, “the eighthintermediate message”) may comprise profanity flagged by the profanitymodule 316 to be ignored, a suggested replacement, or a word or phraseinserted into the message by the profanity module 316 (e.g., in place ofthe identified profanity). In some instances, the eighth intermediatemessage may be the same as the seventh intermediate message (e.g., whenno replacement is performed by the profanity module 316). Depending onthe embodiment, the eighth intermediate message that results from theprofanity module 316 may be provided to another transformation module(in the transformation module 208) for further processing or thesuggested replacement may be provided to the CTT control module 202 todetermine if the message transformed by the profanity module 316 is inthe data store 210. Following operation 618, the eighth intermediatemessage may be provided to the next operation of the transformationmodule 208 for processing. The method 600 may then end.

In accordance with some embodiments, the message that ultimately resultsfrom the transformation module 208 (e.g., the eighth intermediatemessage resulting from operation 618) may subsequently be used to querythe translation data store 210 for a corresponding message, which canserve as a translation for the resulting message. Those skilled in theart will appreciate that in some instances, the message resulting fromthe transformation module 208 (e.g., message subsequently used in thequery to the translation data store 210) may be the same as the initialmessage received (e.g., at operation 602) when no transformation hasbeen applied to the initial message (e.g., the initial message passesthrough operations 604-618 without any transformations being applied).

Those skilled in the art will also appreciate that various embodimentsmay perform more or less operations than the ones shown, may performoperations different from those shown, and may perform operations in adifferent order. Generally, the types of transformation operationsperformed, and the order in which they are performed, may be depend ontransformation strategy employed by the embodiments. As noted herein,various embodiments may implement different transformation/translationstrategies in achieving their respective translations, with certainstrategies being well suited for particular translation applications ortranslation contexts. The transformation/translation strategy employedmay determine which transformation operations are performed, when thetransformation operations are performed, or in what order thetransformation operations are performed. The transformation/translationstrategy may also determine what translations are populated into atranslation data stores, and when a translation data store is utilizedin the overall transformation/translation process.

For some embodiments, the intermediate messages resulting fromoperations in the method 600 may have an impact and/or cascading effecton messages that result from subsequent operations in the method 600.Additionally, for some embodiments, when a chat message is processed bythe method 600, each operations of flow chart 600 may be performed onthe chat message before the method concludes. Alternatively, for someembodiments, the method of flowchart 600 may terminate early upon theperformance of only a subset of the operations shown (e.g., after atleast one operation results in a transformation of the chat message).According to some embodiments, the performance of each operation inflowchart 500 may be followed by a query to the translation data store210 for a corresponding message in the desired language based on thelatest resulting transformed message; in the event a correspondingmessage is identified, the method of flowchart 500 may terminate early.

For various embodiments, the method 600 may perform operations 604-612in parallel. For example, the CTT control module 202 may submit theinitial message to two or more operations 604-612 in parallel, andreceive from each of those two or more operations a separate response.Each response may comprise a flagged text portion, a suggestedreplacement, or a word or phrase inserted into the initial message.Thereafter, the CTT control module 202 may select one of the receivedresponses for subsequent processing (e.g., query a translation datastore 210 or translating by the translation module 116), possiblyaccording to a priority of selection (e.g., which can determine whichtransformed message is selected for further processing and according towhat precedent).

For instance, during the method 600, the CTT control module 202 maysubmit an initial message to operation 604 for identifying chatspeakprocessing, operation 610 for common noun processing, and operation 616for abbreviation processing. In response, operation 604 may return theinitial message transformed for chatspeak, operation 610 may return theinitial message unchanged, and operation 616 may return the initialmessage transformed for abbreviations. Subsequently, based on a priorityof selection, the CTT control module 202 may select the transformedmessage returned from operation 616 for further processing.

For certain embodiments, a time limit may be enforced on performingvarious operations in the method 600. The time limit may cause atransformation operation of method 600 to stop performing if aresponse/result is not received before the time limit has expired. Indoing so, various embodiments may ensure that certain transformationoperations do not unnecessarily hinder the overalltransformation/translation process.

Though the operations of the above method may be depicted and describedin a certain order, those skilled in the art will appreciate that theorder in which the operations are performed may vary betweenembodiments. Additionally, those skilled in the art will appreciate thatthe components described above with respect to the method of theflowchart 600 are merely examples of components that may be used withthe method, and for some embodiments other components may also beutilized in some embodiments.

FIG. 7 is a diagram 700 illustrating an exemplary multi-lingual chatsession, between chat client systems 104 (e.g., 104-1 and 104-2), inaccordance with various embodiments. As shown, the chat client system104-1 may comprise a chat client GUI module 406-1, and the chat clientsystem 104-2 may comprise a chat client GUI module 406-2. As describedherein, each of the chat client GUI modules 406-1 and 406-2 may beconfigured to respectively provide users at chat client systems 104-1and 104-2 with graphical input/output access to chat session sharedbetween them. For some embodiments the chat client GUI modules 406-1 and406-2 may present their respective user with a client GUI adapted forreceiving user interactions with respect to the chat dialogue sent andreceived.

As chat dialogue 712 (represented by two-way arrow in FIG. 7) is passedbetween the chat client systems 104-1 and 104-2, the chat client GUImodules 406-1 and 406-2 may present the chat dialogue 712 in thelanguage (implicitly or explicitly) chosen by the user at theirrespective chat client system 104-1 or 104-2. As shown, the chat clientGUI module 406-1 may comprise a chat dialogue box 702 configured topresent the chat dialogue 712 in a first language (e.g., English) in anoutput area 708 and to receive chat input in the first language in asecond area 710. The chat client GUI module 406-2 may comprise a chatdialogue box 714 configured to present the chat dialogue 712 in a secondlanguage (e.g., French) in an output area 720 and to receive chat inputin the second language in a second area 722. For some embodiments, whenthe chat dialogue 712 is presented in the dialogue boxes 702 and 714, itmay include the presentation of usernames (e.g., user online identifier)associated with the users entering the chat messages in the chatdialogue 712.

In the illustrated embodiment of FIG. 7, the language chosen for thechat client system 104-1 is English and the language chosen for the chatclient system 104-2 is French. Accordingly, chat messages 704 (“LOL”)and 706 (“Who u laughin at?”) are presented in English in the dialoguebox 702 of the chat client GUI module 406-1, while their respectivecounterpart chat messages 716 (“MDR”) and 718 (“Qui to fair rire?”) arepresented in French in the dialogue box 714 of the chat client GUImodule 406-2. The translation of the chat messages 704, 706, 716, and718 may be facilitated through various systems and methods describedherein. More regarding the translation of messages similar to chatmessages 704, 706, 716, and 718 are discussed with respect to FIG. 8-10.

FIG. 8 is a flowchart illustrating operation of an exemplarymulti-lingual communication method 800 in accordance with variousembodiments. As described below, for some embodiments, the method 800may perform operations in connection with the chat client system 104-1,the chat client system 104-2, and the CTT system 114 (e.g., of the chartserver 108). In particular, FIG. 8 illustrates the translation of anEnglish chat message comprising the text “LOL” to a French chat messagein accordance with some embodiments. Such a situation may arise when thelanguage being used by the user at the first chat client system 104-1 isEnglish and the language being used by the user at the second chatclient system 104-2 is French. According to some embodiments, and theCTT system 114 may automatically detect these languagechoices/preferences for the chat client systems 104-1 and 104-2.

As shown, at operation 802, the first chat client system 104-1 maysubmit the English message for transmission to the second chat clientsystem 104-2 (e.g., via the chat host system 112). The English messagemay be routed to the CTT control module 202 of the CTT system 114 fortranslation processing.

At operation 804, the CTT control module 202 may query the translationdata store 210 for a chat message that corresponds to the English chatmessage (“LOL”) and that is pre-translated to French. In response, atoperation 806, the translation data store 210 may return to the CTTcontrol module 202 a corresponding French message (“MDR”) thatcorresponds to the English chat message (“LOL”). Subsequently, atoperation 808, the CTT control module 202 may assist in the transmissionof the corresponding French chat message (“MDR”) to the second chatclient system 104-2 (e.g., CTT system 114 submits the correspondingFrench chat message to the chat host system 112 for transmission).

FIG. 9 is a flowchart illustrating operation of an exemplarymulti-lingual communication method 900 in accordance with variousembodiments. As described below, for some embodiments, the methodillustrated by the flowchart 900 may perform operations in connectionwith the chat client system 104-1, the chat client system 104-2, the CTTsystem 114 (e.g., of the chart server 108), and the translation module116 (e.g., of translation server 110). In particular, FIG. 9 illustratesthe translation of an English chat message comprising the text “LOL” toa French equivalent chat message, in accordance with some embodiments.Unlike the illustrated embodiment of FIG. 8, FIG. 9 illustrates theusage of the transformation module 208 (e.g., of the CTT system 114) andthe translation module 116.

As shown, at operation 902, the first chat client system 104-1 maysubmit the English chat message for transmission to the second chatclient system 104-2 (e.g., via the chat host system 112) with a userthat speaks French. The English chat message may be routed to the CTTcontrol module 202 of the CTT system 114 for translation processing.

At operation 904, the CTT control module 202 may query the translationdata store 210 for a French equivalent chat message that corresponds tothe English chat message (“LOL). In response, at operation 906, thetranslation data store 210 may return a query failure to the CTT controlmodule 202 to indicate that the translation data store 210 does not havea corresponding French chat message for the English chat message(“LOL”). If such is the case, at operation 908, the CTT control module202 may submit the English chat message to the transformation module 208for transformation processing in accordance with certain embodiments. Asdescribed herein, the transformation module 208 may comprise multipletransformation-related modules 932 configured to transform a chatmessage to a message more suitable for further translation processing.

At operation 910, the chatspeak module 302 of the transformation module208 may transform the English chat message (“LOL”) to the transformedEnglish chat message (“laugh out loud”), and may return the transformedEnglish chat message to the CTT control module 202 for furtherprocessing. Those skilled in the art will appreciate that, for someembodiments, the English chat message may be processed by additionalmodules of the transformation module 208 before the transformed Englishchat message is returned to the CTT control module 202.

At operation 912, the CTT control module 202 may query the translationdata store 210 for a French equivalent chat message that corresponds tothe transformed English chat message (“laugh out loud”). In response, atoperation 914, the translation data store 210 may return a query failureto the CTT control module 202 to indicate that the translation datastore 210 does not have a corresponding French chat message for thetransformed English chat message (“laugh out loud”). If such is thecase, at operation 916, the CTT control module 202 may submit thetransformed English chat message to the translation module 116 formachine translation processing in accordance with certain embodiments.

At operation 918, the translation module 116 may return amachine-translated French chat message (“mort de rire”) that correspondsto the transformed English chat message. The resultingmachine-translated French chat message (“mort de rire”) is an example ofa transformed translation of an English chatspeak chat message (“LOL”).

At operation 920, the CTT control module 202 may submit themachine-translated French chat message (“mort de rire”) to thetransformation module 208 for further transformation processing of themachine-translated French chat message in accordance with certainembodiments. As noted herein, the machine-translated text may besubmitted for further transformation processing to further refine theFrench translation. For example, if the original English chat messagecontained English chatspeak, the additional transformation processingcan add, to the extent possible, French chatspeak. Accordingly, atoperation 922, the chatspeak module 302 of the transformation module 208may transform the machine-translated French chat message (“mort derire”) to the transformed French chat message (“MDR”), and may returnthe transformed French chat message to the CTT control module 202 forfurther processing.

Eventually, at operation 924, the CTT control module 202 may assist inthe transmission of the corresponding French chat message (“MDR”) to thesecond chat client system 104-2 (e.g., CTT system 114 submits thecorresponding French chat message to the chat host system 112 fortransmission). Additionally, at operation 926, the CTT control module202 may store a translation mapping in the translation data store 210 ofthe transformed translation between the original English chat message(“LOL”) and the translated French chat message (“MDR”). Once the mappingis stored in the translation data store 210, it may be used to storetranslation entries to speed up future translations, e.g., asillustrated in FIG. 8. As noted herein, the translation data store 210may store mappings of transformed translations and untransformedtranslations.

For some embodiments, the CTT control module 202 may also storeequivalent (transformed and untransformed) translation mappingsdetermined during the operation of the method 900. For certainembodiments, the translation mappings may be between chat message thatwere not original located in the translation data store 210 (e.g., thechat message shown for operation 904, and the chat message shown foroperation 912) and a corresponding message determined during operationssubsequent to the translation data store 210 lookups (e.g., a mappingbetween a query to the translation data store 210 that returns no resultand a corresponding chat message determined after the query, by way ofthe transformation module 208 and/or the translation module 116).

For instance, as shown in FIG. 9, the CTT control module 202 queries thetranslation data store 210 for original English chat message (“LOL” atoperation 904 and the transformed English chat message (“laugh outloud”) at operation 912, both of which resulted in the CTT controlmodule 202 receiving no results from the translation data store 210 (atoperations 906 and 914, respectively). However, at operation 916, theCTT control module 202 eventually submits the transformed Englishmessage (“laugh out loud”) to the machine translation module 116 formachine translation and receives, in response the machine-translatedFrench chat message (“mort de rire”) at operation 918. Accordingly, atoperation 928, the CTT control module 202 may store a translationmapping in the translation data store 210 of the transformed translationbetween the original English chat message (“LOL”) and themachine-translated French chat message (“mort de rire”). Likewise, atoperation 930, the CTT control module 202 may store a translationmapping in the translation data store 210 of the transformed translationbetween the transformed English chat message (“laugh out loud”) and themachine-translated French chat message (“mort de rire”). In doing so,next time method 900 queries the translation data store 210 for theoriginal English chat message (“LOL”) or the transformed English chatmessage (“laugh out loud”), the translation data store 210 will providethe corresponding transformed translations.

FIG. 10 is a flowchart illustrating operation of an exemplarymulti-lingual communication method 1000 in accordance with variousembodiments. As described below, for some embodiments, the method 1000may perform operations in connection with the chat client system 104-1,the chat client system 104-2, the CTT system 114 (e.g., of the chartserver 108), and the translation module 116 (e.g., of the translationserver 110). In particular, FIG. 10 illustrates the translation of anEnglish chat message comprising the text “Who u laughin at?” to a Frenchchat message, in accordance with some embodiments.

As shown, at operation 1002, the first chat client system 104-1 maysubmit the English chat message for transmission to the second chatclient system 104-2 (e.g., via the chat host system 112). The Englishchat message may be routed to the CTT control module 202 of the CTTsystem 114 for translation processing.

At operation 1004, the CTT control module 202 may query the translationdata store 210 for a French equivalent chat message that corresponds tothe English chat message (“Who u laughin at?”). In response, atoperation 1006, the translation data store 210 may return a queryfailure to the CTT control module 202 to indicate that the translationdata store 210 does not have a corresponding French chat message for theEnglish chat message (“Who u laughin at?”). If such is the case, atoperation 1008, the CTT control module 202 may submit the English chatmessage to the transformation module 208 for transformation processingin accordance with certain embodiments. As described herein, thetransformation module 208 may comprise multiple transformation-relatedmodules 1036 configured to transform a chat message to a message moresuitable for further translation processing.

At operation 1010, the chatspeak module 302 of the transformation module208 may transform the English chat message (“Who u laughin at?”) to thetransformed English chat message (“Who you laughin at?”), and pass onthe transformed English chat message to additional modules of thetransformation module 208 for further processing, such as the spellingcheck module 312.

As discussed herein, various modules of transformation module 208,including the chatspeak module 302, may be configured to identify one ormore words or phrases in a chat message and suggest replacement words orphrases for the identified words or phrases. Accordingly, those skilledin the art would appreciate that for some embodiments, thetransformation performed/suggested by a module of transformation module208 may involve a word-to-phrase or a phrase-to-phrase transformation ofthe chat message. For example, at operation 1010, the chatspeak module302 may alternatively transform the English chat message (“Who u laughinat?”) to the transformed English chat message (“Who are you laughingat?”), possibly by replacing/suggesting the replacement of the phrase“who u” with “who are you” during the transformation (followed by thereplacement/suggestion of the replacing the word “laughin” with“laughing”). In doing so, various modules of the transformation module208, such as the chatspeak module 302, may provide grammaticalimprovements to their respective transformations, while possiblyobviating the need for a separate module in the transformation module208 to implement grammar improvements.

For some embodiments, before the transformed English chat message ispassed on to additional modules of the transformation module 208, thechatspeak module 302 may pass on the transformed English chat message tothe CTT control module 202 at operation 1010. In turn, the CTT controlmodule 202 may query the translation data store 210 (at operation 1012)for a French equivalent chat message that corresponds to the transformedEnglish chat message (“Who you laughin at?”). In response, at operation1014, the translation data store 210 may return a query failure to theCTT control module 202 to indicate that the translation data store 210does not have a corresponding French chat message for the transformedEnglish chat message (“Who you laughin at?”).

At operation 1016, the spelling check module 312 may perform a spellcheck process on the transformed English chat message (“Who you laughinat?”) at operation 1018. During the spell check process, the spellingcheck module 312 may correct the transformed English chat message to acorrected English chat message (“Who you laughing at?”), and may returnthe corrected English chat message to the CTT control module 202. Thoseskilled in the art will appreciate that for some embodiments, thecorrected English chat message may processed by additional modules ofthe transformation module 208 before the transformed English chatmessage is returned to the CTT control module 202.

At operation 1020, the CTT control module 202 may query the translationdata store 210 for a French equivalent chat message that corresponds tothe corrected English chat message (“Who you laughing at?”). Inresponse, at operation 1022, the translation data store 210 may return aquery failure to the CTT control module 202 to indicate that thetranslation data store 210 does not have a corresponding French chatmessage for the corrected English chat message (“Who you laughing at?”).If such is the case, at operation 1024, the CTT control module 202 maysubmit the corrected English chat message to the translation module 116for machine translation processing in accordance with certainembodiments.

At operation 1026, the translation module 116 may return amachine-translated French chat message (“Qui te fait rire?”) thatcorresponds to the corrected English chat message. At operation 1028,the CTT control module 202 may submit the machine-translated French chatmessage (“Qui te fait rire?”) to the transformation module 208 forfurther transformation processing of the machine-translated French chatmessage in accordance with certain embodiments.

As noted herein, the machine-translated text may be submitted forfurther transformation processing to further refine the translation ofthe text. For example, if the original English chat message containedEnglish chatspeak, the additional transformation processing can add, tothe extent possible, French chatspeak. At operation 1030, thetransformation module 208 may return the machine-translated French chatmessage (“Qui te fait rire?”) unchanged to the CTT control module 202for further processing (e.g., when the modules of the transformationmodule 208 do not apply any changes to the machine-translated Frenchchat message).

At operation 1032, the CTT control module 202 may assist in thetransmission of the machine-translated French chat message (“Qui te faitrire?”) to the second chat client system 104-2 (e.g., CTT system 114submits the corresponding French chat message to the chat host system112 for transmission). Additionally, at operation 1034, the CTT controlmodule 202 may store a translation mapping in the translation data store210 between the original English chat message (“Who u laughin at?”) andthe translated French chat message (“Qui te fait rire?”). As describedherein, in additional operations (not shown), the CTT control module 202may also store equivalent translation mappings in the translation datastore 210 based on previously failed queries to the translation datastore 210 and corresponding messages determined subsequent to thosequeries (e.g., similar to operations 928 and 930 in FIG. 9).

According to some embodiments, the transformation operations performedby the transformation module 208 may comprise performing certaintransformation operations in parallel, and perform certaintransformation operations in serial. The order in which transformationoperations are performed in parallel and in serial may vary betweenvarious embodiments. As described herein, where the transformationoperations are performed in parallel, some embodiments may employ apriority of selection to determine which transformed message is selectedfor further processing and according to what precedent.

FIG. 11 is a flowchart illustrating operation of an exemplarymulti-lingual communication method 1100 in accordance with variousembodiments. As described below, for some embodiments, the method 1100may perform operations in connection with the chat client system 104-1,the chat client system 104-2, the CTT system 114 (e.g., of the chartserver 108), and the translation module 116 (e.g., of the translationserver 110). In particular, FIG. 11 illustrates the translation of anEnglish chat message comprising the text “Who u laughin at?” to a Frenchchat message by parallel transformation operations, in accordance withsome embodiments.

As shown, at operation 1102, the first chat client system 104-1 maysubmit the English chat message for transmission to the second chatclient system 104-2 (e.g., via the chat host system 112). The Englishchat message may be routed to the CTT control module 202 of the CTTsystem 114 for translation processing.

At operation 1104, the CTT control module 202 may query the translationdata store 210 for a French equivalent chat message that corresponds tothe English chat message (“Who u laughin at?”). In response, atoperation 1106, the translation data store 210 may return a queryfailure to the CTT control module 202 to indicate that the translationdata store 210 does not have a corresponding French chat message for theEnglish chat message (“Who u laughin at?”).

If such is the case, the CTT control module 202 may submit the Englishchat message to the transformation module 208 for transformationprocessing in accordance with certain embodiments. As described herein,the transformation module 208 may comprise multipletransformation-related modules 1130 configured to transform a chatmessage to a message more suitable for further translation processing.As shown in FIG. 11, during operations 1108, the CTT control module 202may submit the English chat message (“Who u laughin at?”), in parallel,to two or more transformation-related modules 1130 of the transformationmodule 208. Additionally, during operations 1108, the CTT control module202 may be receiving results from the transformation-related modules1130 in parallel, and submitting queries to the translation data store210, based on the transformation results, in parallel.

Accordingly, at operation 1110 a, the CTT control module 202 may submitthe English chat message (“Who u laughin at?”) to the chatspeak module302 for transformation processing. In parallel, at operation 1110 b, theCTT control module 202 may submit the English chat message (“Who ulaughin at?”) to the spelling check module 312 for transformationprocessing. Subsequently, the CTT control module 202 may receive a firsttransformed English chat message (“Who you laughin at?”) from thechatspeak module 302 at operation 1112 a, while at operation 1112 b theCTT control module 202 may receive a second transformed English chatmessage (“Who u laughing at?”) from the spelling check module 312.Depending on their respective transformation processing times, thechatspeak module 302, the spelling check module 312, and the othertransformation-related modules 1130 may respond to the CTT controlmodule 202 in serial or in parallel with respect to one another.

Subsequently, at operation 1114 a, the CTT control module 202 may querythe translation data store 210 for a French equivalent chat message thatcorresponds to the first transformed English chat message (“Who youlaughin at?”). At operation 1114 b, the CTT control module 202 may querythe translation data store 210 for a French equivalent chat message thatcorresponds to the second transformed English chat message (“Who ulaughing at?”). For some embodiments, during operations 1114 a and 1114b, the CTT control module 202 may query the translation data store 210in serial or in parallel. In some embodiments, the timings of thequeries may depend on when the transformation-related modules 1130 ofthe transformation module 208 return their respective responses. Asshown in FIG. 11, the translation data store 210 may return a queryfailure (e.g., <FAIL>) for the queries at operations 1116 a and 1116 b.

Eventually, the CTT control module 202 may select one transformedmessage, from the two or more messages that result from the paralleloperations 1108, for further processing. Where only one of thetransformation-related modules 1130 results in a transformed message,the CTT control module 202 may select that particular transformedmessage for further processing. As noted herein, the CTT control module202 may select a transformed message based on a priority of selection,which may be determined according to the transformation/translationstrategy selected by the embodiments. For some embodiments, the priorityof selection may be based on whether the transformed message has themost formal content, the transformed message has the mosttransformations, or the transformed message results from atransformation-related module known for having a high likelihood ofproducing a transformed message suitable for machine-translation.

Once a transformed message has been selected, at operation 1118, the CTTcontrol module 202 may submit the transformed English chat message tothe translation module 116 for machine translation processing inaccordance with certain embodiments. For example, as shown in FIG. 11,the CTT control module 202 may select the first transformed English chatmessage produced by the chatspeak module 302 (“Who you laughin at?”) forsubmission to the translation module 116.

At operation 1120, the translation module 116 may return amachine-translated French chat message (“Qui te fait rire?”) thatcorresponds to the first transformed English chat message (and despitecomprising the misspelled word “laughin”). At operation 1122, the CTTcontrol module 202 may submit the machine-translated French chat message(“Qui te fait rire?”) to the transformation module 208 for furthertransformation processing of the machine-translated French chat messagein accordance with certain embodiments.

As noted herein, the machine-translated text may be submitted forfurther transformation processing to further refine the translation ofthe text. For example, if the original English chat message containedEnglish chatspeak, the additional transformation processing can add, tothe extent possible, French chatspeak. At operation 1124, thetransformation module 208 may return the machine-translated French chatmessage (“Qui te fait rire?”) unchanged to the CTT control module 202for further processing (e.g., when the modules of the transformationmodule 208 do not apply any changes to the machine-translated Frenchchat message).

At operation 1126, the CTT control module 202 may assist in thetransmission of the machine-translated French chat message (“Qui te faitrire?”) to the second chat client system 104-2 (e.g., CTT system 114submits the corresponding French chat message to the chat host system112 for transmission). Additionally, at operation 1128, the CTT controlmodule 202 may store a translation mapping in the translation data store210 between the original English chat message (“Who u laughin at?”) andthe translated French chat message (“Qui te fait rire?”). As describedherein, in additional operations (not shown), the CTT control module 202may also store equivalent translation mappings in the translation datastore 210 based on previously failed queries to the translation datastore 210 and corresponding messages determined subsequent to thosequeries (e.g., similar to operations 928 and 930 in FIG. 9).

For some embodiments, the transformation operations may be performed ina hybrid serial/parallel arrangement, whereby some transformationoperations are performed in parallel and other transformation operationsare performed in serial. For example, as shown in FIG. 11, the Englishchat message (“Who u laughin at?”) is submitted to the chat speak module302 and spelling check module 312 in parallel at operations 1110 a and1110 b. Subsequently, once one of the resulting transformed messages isselected (e.g., based on a priority of selection), the othertransformation-related modules 1130 of the transformation module 208(e.g., the acronym module 304, the proper noun module 306, and thecommon noun module 308) may operate on the selected transformed messagein parallel.

FIG. 12 is a block diagram of an exemplary digital device 1200. Thedigital device 1200 comprises a processor 1202, a memory system 1204, astorage system 1206, a communication network interface 1208, an I/Ointerface 1210, and a display interface 1212 communicatively coupled toa bus 1214. The processor 1202 is configured to execute executableinstructions (e.g., programs). In some embodiments, the processor 1202comprises circuitry or any processor capable of processing theexecutable instructions.

The memory system 1204 is any memory configured to store data. Someexamples of the memory system 1204 are storage devices, such as RAM orROM. The memory system 1204 can comprise the ram cache. In variousembodiments, data is stored within the memory system 1204. The datawithin the memory system 1204 may be cleared or ultimately transferredto the storage system 1206.

The storage system 1206 is any storage configured to retrieve and storedata. Some examples of the storage system 1206 are flash drives, harddrives, optical drives, and/or magnetic tape. In some embodiments, thedigital device 1200 includes a memory system 1204 in the form of RAM anda storage system 1206 in the form of flash data. Both the memory system1204 and the storage system 1206 comprise computer readable media whichmay store instructions or programs that are executable by a computerprocessor including the processor 1202.

The communications network interface (com. network interface) 1208 canbe coupled to a network (e.g., the computer network 106) via the link1216. The communication network interface 1208 may support communicationover an Ethernet connection, a serial connection, a parallel connection,or an ATA connection, for example. The communication network interface1208 may also support wireless communication (e.g., 802.11 a/b/g/n,WiMax). It will be apparent to those skilled in the art that thecommunication network interface 1208 can support many wired and wirelessstandards.

The optional input/output (I/O) interface 1210 is any device thatreceives input from the user and output data. The optional displayinterface 1212 is any device that is configured to output graphics anddata to a display. In one example, the display interface 1212 is agraphics adapter.

It will be appreciated by those skilled in the art that the hardwareelements of the digital device 1200 are not limited to those depicted inFIG. 12. A digital device 1200 may comprise more or less hardwareelements than those depicted. Further, hardware elements may sharefunctionality and still be within various embodiments described herein.In one example, encoding and/or decoding may be performed by theprocessor 1202 and/or a co-processor located on a GPU (i.e., Nvidia®).

The above-described functions and components can be comprised ofinstructions that are stored on a storage medium such as a computerreadable medium. The instructions can be retrieved and executed by aprocessor. Some examples of instructions are software, program code, andfirmware. Some examples of storage medium are memory devices, tape,disks, integrated circuits, and servers. The instructions areoperational when executed by the processor to direct the processor tooperate in accord with some embodiments. Those skilled in the art arefamiliar with instructions, processor(s), and storage medium.

Various embodiments are described herein as examples. It will beapparent to those skilled in the art that various modifications may bemade and other embodiments can be used without departing from thebroader scope of the invention(s) presented herein. These and othervariations upon the exemplary embodiments are intended to be covered bythe present invention(s).

What is claimed is:
 1. A method using one or more computer processors,comprising: providing, using the one or more computer processors, afirst message in a first language to a first transformation module in asequence of computer-implemented transformation modules, eachtransformation module comprising executable instructions configured tobe executed by the one or more computer processors for performingmessage transformation operations, wherein each subsequenttransformation module in the sequence accepts, as input, an output of apreceding transformation module in the sequence and provides, as output,a respective transformed message, wherein at least one transformationmodule in the sequence identifies at least a portion of the output ofthe at least one transformation module as not to be transformed bysubsequent transformation modules in the sequence, and wherein theoutput of a final transformation module in the sequence comprises atransformed message in the first language; and querying, using the oneor more computer processors, a computer data store for a translation ofthe transformed message in a second language.
 2. The method of claim 1,wherein the first message is received from a chat system.
 3. The methodof claim 1, wherein the first message is provided to the firsttransformation module when the data store does not include a translationof the first message in the second language.
 4. The method of claim 1,wherein one or more transformation modules (i) identify a chatspeak wordor phrase in the first message and (ii) replace the chatspeak word orphrase with a non-chatspeak word or phrase.
 5. The method of claim 1,wherein one or more transformation modules perform a spelling check onthe first message.
 6. The method of claim 1, wherein one or moretransformation modules (i) identify an abbreviation in the first messageand (ii) replace the abbreviation with a word or a phrase correspondingto the abbreviation.
 7. The method of claim 1, wherein one or moretransformation modules (i) identify an acronym in the first message and(ii) replace the acronym with a word or a phrase corresponding to theacronym.
 8. The method of claim 1, wherein one or more transformationmodules (i) identify a colloquial word or phrase in the first messageand (ii) replace the colloquial word or phrase with a word or a phraserepresenting the colloquial word or phrase.
 9. The method of claim 1,wherein one or more transformation modules (i) identify a profane wordor phrase in the first message and (ii) replace the profane word orphrase with a non-profane word or phrase or remove the profane word orphrase.
 10. The method of claim 1, wherein the first message comprisesone of a text message, an emoticon, and a part of a larger message. 11.A system, comprising: one or more computer processors programmed toperform operations to: provide, using the one or more computerprocessors, a first message in a first language to a firsttransformation module in a sequence of computer-implementedtransformation modules, each transformation module comprising executableinstructions configured to be executed by the one or more computerprocessors for performing message transformation operations, whereineach subsequent transformation module in the sequence accepts, as input,an output of a preceding transformation module in the sequence andprovides, as output, a respective transformed message, wherein at leastone transformation module in the sequence identifies at least a portionof the output of the at least one transformation module as not to betransformed by subsequent transformation modules in the sequence, andwherein the output of a final transformation module in the sequencecomprises a transformed message in the first language; and query, usingthe one or more computer processors, a computer data store for atranslation of the transformed message in a second language.
 12. Thesystem of claim 11, wherein the first message is received from a chatsystem.
 13. The system of claim 11, wherein the first message isprovided to the first transformation module when the data store does notinclude a translation of the first message in the second language. 14.The system of claim 11, wherein one or more transformation modules (i)identify a chatspeak word or phrase in the first message and (ii)replace the chatspeak word or phrase with a non-chatspeak word orphrase.
 15. The system of claim 11, wherein one or more transformationmodules perform a spelling check on the first message.
 16. The system ofclaim 11, wherein one or more transformation modules (i) identify anabbreviation in the first message and (ii) replace the abbreviation witha word or a phrase corresponding to the abbreviation.
 17. The system ofclaim 11, wherein one or more transformation modules (i) identify anacronym in the first message and (ii) replace the acronym with a word ora phrase corresponding to the acronym.
 18. The system of claim 11,wherein one or more transformation modules (i) identify a colloquialword or phrase in the first message and (ii) replace the colloquial wordor phrase with a word or a phrase representing the colloquial word orphrase.
 19. The system of claim 11, wherein one or more transformationmodules (i) identify a profane word or phrase in the first message and(ii) replace the profane word or phrase with a non-profane word orphrase or remove the profane word or phrase.
 20. A non-transitorycomputer-readable medium having instructions stored thereon that, whenexecuted by one or more computer processors, cause the computerprocessors to: provide, using the one or more computer processors, afirst message in a first language to a first transformation module in asequence of computer-implemented transformation modules, eachtransformation module comprising executable instructions configured tobe executed by the one or more computer processors for performingmessage transformation operations, wherein each subsequenttransformation module in the sequence accepts, as input, an output of apreceding transformation module in the sequence and provides, as output,a respective transformed message, wherein at least one transformationmodule in the sequence identifies at least a portion of the output ofthe at least one transformation module as not to be transformed bysubsequent transformation modules in the sequence, and wherein theoutput of a final transformation module in the sequence comprises atransformed message in the first language; and query, using the one ormore computer processors, a computer data store for a translation of thetransformed message in a second language.